Switch from cached_download to hf_hub_download in remaining occurrences (#31284)

Switch from hf_hub_url to hf_hub_download in remaining occurences

docs/source/en/tasks/semantic_segmentation.md

@@ -245,11 +245,12 @@ You'll also want to create a dictionary that maps a label id to a label class wh
 
 ```py
 >>> import json
->>> from huggingface_hub import cached_download, hf_hub_url
+>>> from pathlib import Path
+>>> from huggingface_hub import hf_hub_download
 
 >>> repo_id = "huggingface/label-files"
 >>> filename = "ade20k-id2label.json"
->>> id2label = json.load(open(cached_download(hf_hub_url(repo_id, filename, repo_type="dataset")), "r"))
+>>> id2label = json.loads(Path(hf_hub_download(repo_id, filename, repo_type="dataset")).read_text())
 >>> id2label = {int(k): v for k, v in id2label.items()}
 >>> label2id = {v: k for k, v in id2label.items()}
 >>> num_labels = len(id2label)

docs/source/ja/tasks/semantic_segmentation.md

@@ -83,11 +83,12 @@ pip install -q datasets transformers evaluate
 
 ```py
 >>> import json
->>> from huggingface_hub import cached_download, hf_hub_url
+>>> from pathlib import Path
+>>> from huggingface_hub import hf_hub_download
 
 >>> repo_id = "huggingface/label-files"
 >>> filename = "ade20k-id2label.json"
->>> id2label = json.load(open(cached_download(hf_hub_url(repo_id, filename, repo_type="dataset")), "r"))
+>>> id2label = json.loads(Path(hf_hub_download(repo_id, filename, repo_type="dataset")).read_text())
 >>> id2label = {int(k): v for k, v in id2label.items()}
 >>> label2id = {v: k for k, v in id2label.items()}
 >>> num_labels = len(id2label)

docs/source/ja/tasks/sequence_classification.md

@@ -83,11 +83,12 @@ pip install -q datasets transformers evaluate
 
 ```py
 >>> import json
->>> from huggingface_hub import cached_download, hf_hub_url
+>>> from pathlib import Path
+>>> from huggingface_hub import hf_hub_download
 
 >>> repo_id = "huggingface/label-files"
 >>> filename = "ade20k-id2label.json"
->>> id2label = json.load(open(cached_download(hf_hub_url(repo_id, filename, repo_type="dataset")), "r"))
+>>> id2label = json.loads(Path(hf_hub_download(repo_id, filename, repo_type="dataset")).read_text())
 >>> id2label = {int(k): v for k, v in id2label.items()}
 >>> label2id = {v: k for k, v in id2label.items()}
 >>> num_labels = len(id2label)

docs/source/ko/tasks/semantic_segmentation.md

@@ -82,11 +82,12 @@ pip install -q datasets transformers evaluate
 
 ```py
 >>> import json
->>> from huggingface_hub import cached_download, hf_hub_url
+>>> from pathlib import Path
+>>> from huggingface_hub import hf_hub_download
 
 >>> repo_id = "huggingface/label-files"
 >>> filename = "ade20k-id2label.json"
->>> id2label = json.load(open(cached_download(hf_hub_url(repo_id, filename, repo_type="dataset")), "r"))
+>>> id2label = json.loads(Path(hf_hub_download(repo_id, filename, repo_type="dataset")).read_text())
 >>> id2label = {int(k): v for k, v in id2label.items()}
 >>> label2id = {v: k for k, v in id2label.items()}
 >>> num_labels = len(id2label)